knit_by_pkgdown <- !is.null(knitr::opts_chunk$get("fig.retina"))
knitr::opts_chunk$set(
  warning = TRUE, # show warnings during codebook generation
  message = TRUE, # show messages during codebook generation
  error = TRUE, # do not interrupt codebook generation in case of errors,
                # TRUE is usually better for debugging
  echo = TRUE  # show R code
)
ggplot2::theme_set(ggplot2::theme_bw())
## Warning: As of rlang 0.4.0, dplyr must be at least version 0.8.0.
## x dplyr 0.7.8 is too old for rlang 0.4.4.
## i Please update dplyr to the latest version.
## i Updating packages on Windows requires precautions:
##   <https://github.com/jennybc/what-they-forgot/issues/62>

Loading data

library(readr); library(data.table); library(tidyr); library(dplyr); library(codebook); library(labelled)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:data.table':
## 
##     between, first, last
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
## 
## LABELLED 2.0.0: BREAKING CHANGE
## 
## Following version 2.0.0 of `haven`, `labelled()` and `labelled_spss()` now produce objects with class 'haven_labelled' and 'haven_labelled_spss', due to conflict between the previous 'labelled' class and the 'labelled' class used by `Hmisc`.
## 
## A new function `update_labelled()` could be used to convert data imported with an older version of `haven`/`labelled` to the new classes.
url <- 'https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip'
download.file(url, destfile = 'data.zip')
unzip("data.zip")
header <- read.table('Mod3/UCI HAR Dataset/features.txt', header = F, stringsAsFactors = F)
req_cols <- grep(paste('mean()|std()',collapse="|"), header[, 2])

df.test <- fread(file = 'Mod3/UCI HAR Dataset/test/X_test.txt', header = F, blank.lines.skip = T, stringsAsFactors = F, select = req_cols)
names(df.test) <- header[req_cols, 2]
df.test.y <- fread(file = 'Mod3/UCI HAR Dataset/test/y_test.txt', header = F, blank.lines.skip = T, stringsAsFactors = F, col.names = ('Activity_Name'))
df.test.sub <- fread(file = 'Mod3/UCI HAR Dataset/test/subject_test.txt', header = F, blank.lines.skip = T, stringsAsFactors = F, col.names = ('Subject_Name'))
df.test <- cbind(df.test.sub, df.test.y, df.test)
df.train <- fread(file = 'Mod3/UCI HAR Dataset/train/X_train.txt', header = F, blank.lines.skip = T, stringsAsFactors = F, select = req_cols)
names(df.train) <- header[req_cols, 2]
df.train.y <- fread(file = 'Mod3/UCI HAR Dataset/train/y_train.txt', header = F, blank.lines.skip = T, stringsAsFactors = F, col.names = ('Activity_Name'))
df.train.sub <- fread(file = 'Mod3/UCI HAR Dataset/train/subject_train.txt', header = F, blank.lines.skip = T, stringsAsFactors = F, col.names = ('Subject_Name'))
df.train <- cbind(df.train.sub, df.train.y, df.train)
final <- rbind(df.train, df.test)
rm('df.test', 'df.train','df.test.y', 'df.train.y', 'url', 'df.test.sub', 'df.train.sub')

final.avg <- final %>% group_by(Subject_Name, Activity_Name) %>% 
  summarize_at(vars(-c(Subject_Name, Activity_Name)), mean)
## Warning: The `printer` argument is deprecated as of rlang 0.3.0.
## This warning is displayed once per session.
write.table(final.avg, 'final.avg.txt', row.names = F)

Adding and changing metadata

Variable labels

## Warning in `[<-.data.table`(x, j = name, value = value): Adding new column
## 'V1' then assigning NULL (deleting it).

The Codebook

## No missing values.

Metadata

Description

Dataset name: Human Activity Recognition Using Smartphones Data Set

The experiments have been carried out with a group of 30 volunteers within an age bracket of 19-48 years. Each person performed six activities (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING) wearing a smartphone (Samsung Galaxy S II) on the waist. Using its embedded accelerometer and gyroscope, we captured 3-axial linear acceleration and 3-axial angular velocity at a constant rate of 50Hz. The experiments have been video-recorded to label the data manually. The obtained dataset has been randomly partitioned into two sets, where 70% of the volunteers was selected for generating the training data and 30% the test data.

The sensor signals (accelerometer and gyroscope) were pre-processed by applying noise filters and then sampled in fixed-width sliding windows of 2.56 sec and 50% overlap (128 readings/window). The sensor acceleration signal, which has gravitational and body motion components, was separated using a Butterworth low-pass filter into body acceleration and gravity. The gravitational force is assumed to have only low frequency components, therefore a filter with 0.3 Hz cutoff frequency was used. From each window, a vector of features was obtained by calculating variables from the time and frequency domain.

Check the README.txt file for further details about this dataset.

A video of the experiment including an example of the 6 recorded activities with one of the participants can be seen in the following link: [Web Link]

An updated version of this dataset can be found at [Web Link]. It includes labels of postural transitions between activities and also the full raw inertial signals instead of the ones pre-processed into windows.

  • Citation: Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. A Public Domain Dataset for Human Activity Recognition Using Smartphones. 21th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013. Bruges, Belgium 24-26 April 2013.

  • URL: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones

  • Date published: 2020-07-27

  • Creator:Sandeep Kiran Gudla

    • keywords: Subject_Name, Activity_Name, tBodyAcc-mean()-X, tBodyAcc-mean()-Y, tBodyAcc-mean()-Z, tBodyAcc-std()-X, tBodyAcc-std()-Y, tBodyAcc-std()-Z, tGravityAcc-mean()-X, tGravityAcc-mean()-Y, tGravityAcc-mean()-Z, tGravityAcc-std()-X, tGravityAcc-std()-Y, tGravityAcc-std()-Z, tBodyAccJerk-mean()-X, tBodyAccJerk-mean()-Y, tBodyAccJerk-mean()-Z, tBodyAccJerk-std()-X, tBodyAccJerk-std()-Y, tBodyAccJerk-std()-Z, tBodyGyro-mean()-X, tBodyGyro-mean()-Y, tBodyGyro-mean()-Z, tBodyGyro-std()-X, tBodyGyro-std()-Y, tBodyGyro-std()-Z, tBodyGyroJerk-mean()-X, tBodyGyroJerk-mean()-Y, tBodyGyroJerk-mean()-Z, tBodyGyroJerk-std()-X, tBodyGyroJerk-std()-Y, tBodyGyroJerk-std()-Z, tBodyAccMag-mean(), tBodyAccMag-std(), tGravityAccMag-mean(), tGravityAccMag-std(), tBodyAccJerkMag-mean(), tBodyAccJerkMag-std(), tBodyGyroMag-mean(), tBodyGyroMag-std(), tBodyGyroJerkMag-mean(), tBodyGyroJerkMag-std(), fBodyAcc-mean()-X, fBodyAcc-mean()-Y, fBodyAcc-mean()-Z, fBodyAcc-std()-X, fBodyAcc-std()-Y, fBodyAcc-std()-Z, fBodyAcc-meanFreq()-X, fBodyAcc-meanFreq()-Y, fBodyAcc-meanFreq()-Z, fBodyAccJerk-mean()-X, fBodyAccJerk-mean()-Y, fBodyAccJerk-mean()-Z, fBodyAccJerk-std()-X, fBodyAccJerk-std()-Y, fBodyAccJerk-std()-Z, fBodyAccJerk-meanFreq()-X, fBodyAccJerk-meanFreq()-Y, fBodyAccJerk-meanFreq()-Z, fBodyGyro-mean()-X, fBodyGyro-mean()-Y, fBodyGyro-mean()-Z, fBodyGyro-std()-X, fBodyGyro-std()-Y, fBodyGyro-std()-Z, fBodyGyro-meanFreq()-X, fBodyGyro-meanFreq()-Y, fBodyGyro-meanFreq()-Z, fBodyAccMag-mean(), fBodyAccMag-std(), fBodyAccMag-meanFreq(), fBodyBodyAccJerkMag-mean(), fBodyBodyAccJerkMag-std(), fBodyBodyAccJerkMag-meanFreq(), fBodyBodyGyroMag-mean(), fBodyBodyGyroMag-std(), fBodyBodyGyroMag-meanFreq(), fBodyBodyGyroJerkMag-mean(), fBodyBodyGyroJerkMag-std() and fBodyBodyGyroJerkMag-meanFreq()

Variables

Subject_Name

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
Subject_Name integer 0 10299 10299 16.15 8.68 1 9 17 24 30 ▇▆▅▇▇▆▇▇

Activity_Name

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
Activity_Name integer 0 10299 10299 3.62 1.74 1 2 4 5 6 ▇▆▁▆▇▁▇▇

tBodyAcc-mean()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAcc-mean()-X numeric 0 10299 10299 0.27 0.068 -1 0.26 0.28 0.29 1 ▁▁▁▁▂▇▁▁

tBodyAcc-mean()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAcc-mean()-Y numeric 0 10299 10299 -0.018 0.037 -1 -0.025 -0.017 -0.011 1 ▁▁▁▇▁▁▁▁

tBodyAcc-mean()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAcc-mean()-Z numeric 0 10299 10299 -0.11 0.053 -1 -0.12 -0.11 -0.098 1 ▁▁▁▇▁▁▁▁

tBodyAcc-std()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAcc-std()-X numeric 0 10299 10299 -0.61 0.44 -1 -0.99 -0.94 -0.25 1 ▇▁▃▂▁▁▁▁

tBodyAcc-std()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAcc-std()-Y numeric 0 10299 10299 -0.51 0.5 -1 -0.98 -0.84 -0.057 1 ▇▁▁▃▂▁▁▁

tBodyAcc-std()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAcc-std()-Z numeric 0 10299 10299 -0.61 0.4 -1 -0.98 -0.85 -0.28 1 ▇▁▃▂▁▁▁▁

tGravityAcc-mean()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tGravityAcc-mean()-X numeric 0 10299 10299 0.67 0.52 -1 0.81 0.92 0.95 1 ▁▁▁▁▁▁▁▇

tGravityAcc-mean()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tGravityAcc-mean()-Y numeric 0 10299 10299 0.004 0.38 -1 -0.24 -0.14 0.12 1 ▁▁▅▇▂▁▁▂

tGravityAcc-mean()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tGravityAcc-mean()-Z numeric 0 10299 10299 0.092 0.33 -1 -0.12 0.037 0.22 1 ▁▁▂▇▇▂▂▂

tGravityAcc-std()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tGravityAcc-std()-X numeric 0 10299 10299 -0.97 0.078 -1 -0.99 -0.98 -0.96 1 ▇▁▁▁▁▁▁▁

tGravityAcc-std()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tGravityAcc-std()-Y numeric 0 10299 10299 -0.95 0.085 -1 -0.99 -0.98 -0.95 1 ▇▁▁▁▁▁▁▁

tGravityAcc-std()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tGravityAcc-std()-Z numeric 0 10299 10299 -0.94 0.1 -1 -0.99 -0.97 -0.93 1 ▇▁▁▁▁▁▁▁

tBodyAccJerk-mean()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAccJerk-mean()-X numeric 0 10299 10299 0.079 0.18 -1 0.063 0.076 0.091 1 ▁▁▁▂▇▁▁▁

tBodyAccJerk-mean()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAccJerk-mean()-Y numeric 0 10299 10299 0.0079 0.16 -1 -0.019 0.011 0.034 1 ▁▁▁▃▇▁▁▁

tBodyAccJerk-mean()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAccJerk-mean()-Z numeric 0 10299 10299 -0.0047 0.16 -1 -0.032 -0.0012 0.025 1 ▁▁▁▇▇▁▁▁

tBodyAccJerk-std()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAccJerk-std()-X numeric 0 10299 10299 -0.64 0.41 -1 -0.99 -0.95 -0.29 1 ▇▁▃▂▁▁▁▁

tBodyAccJerk-std()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAccJerk-std()-Y numeric 0 10299 10299 -0.61 0.43 -1 -0.99 -0.93 -0.22 1 ▇▁▂▂▁▁▁▁

tBodyAccJerk-std()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAccJerk-std()-Z numeric 0 10299 10299 -0.76 0.28 -1 -0.99 -0.95 -0.55 1 ▇▃▂▁▁▁▁▁

tBodyGyro-mean()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyro-mean()-X numeric 0 10299 10299 -0.031 0.18 -1 -0.046 -0.028 -0.011 1 ▁▁▁▇▂▁▁▁

tBodyGyro-mean()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyro-mean()-Y numeric 0 10299 10299 -0.075 0.13 -1 -0.1 -0.075 -0.051 1 ▁▁▁▇▂▁▁▁

tBodyGyro-mean()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyro-mean()-Z numeric 0 10299 10299 0.088 0.13 -1 0.065 0.086 0.11 1 ▁▁▁▁▇▁▁▁

tBodyGyro-std()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyro-std()-X numeric 0 10299 10299 -0.72 0.3 -1 -0.99 -0.9 -0.48 1 ▇▃▃▁▁▁▁▁

tBodyGyro-std()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyro-std()-Y numeric 0 10299 10299 -0.68 0.36 -1 -0.98 -0.91 -0.45 1 ▇▂▂▁▁▁▁▁

tBodyGyro-std()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyro-std()-Z numeric 0 10299 10299 -0.65 0.37 -1 -0.99 -0.88 -0.34 1 ▇▁▃▂▁▁▁▁

tBodyGyroJerk-mean()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyroJerk-mean()-X numeric 0 10299 10299 -0.097 0.13 -1 -0.12 -0.098 -0.079 1 ▁▁▁▇▁▁▁▁

tBodyGyroJerk-mean()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyroJerk-mean()-Y numeric 0 10299 10299 -0.042 0.11 -1 -0.059 -0.041 -0.025 1 ▁▁▁▇▂▁▁▁

tBodyGyroJerk-mean()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyroJerk-mean()-Z numeric 0 10299 10299 -0.055 0.13 -1 -0.079 -0.055 -0.032 1 ▁▁▁▇▂▁▁▁

tBodyGyroJerk-std()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyroJerk-std()-X numeric 0 10299 10299 -0.73 0.3 -1 -0.99 -0.93 -0.49 1 ▇▂▃▁▁▁▁▁

tBodyGyroJerk-std()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyroJerk-std()-Y numeric 0 10299 10299 -0.79 0.27 -1 -0.99 -0.95 -0.63 1 ▇▃▁▁▁▁▁▁

tBodyGyroJerk-std()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyroJerk-std()-Z numeric 0 10299 10299 -0.74 0.3 -1 -0.99 -0.95 -0.51 1 ▇▃▂▁▁▁▁▁

tBodyAccMag-mean()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAccMag-mean() numeric 0 10299 10299 -0.55 0.47 -1 -0.98 -0.87 -0.12 1 ▇▁▁▃▂▁▁▁

tBodyAccMag-std()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAccMag-std() numeric 0 10299 10299 -0.59 0.43 -1 -0.98 -0.84 -0.24 1 ▇▁▃▂▁▁▁▁

tGravityAccMag-mean()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tGravityAccMag-mean() numeric 0 10299 10299 -0.55 0.47 -1 -0.98 -0.87 -0.12 1 ▇▁▁▃▂▁▁▁

tGravityAccMag-std()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tGravityAccMag-std() numeric 0 10299 10299 -0.59 0.43 -1 -0.98 -0.84 -0.24 1 ▇▁▃▂▁▁▁▁

tBodyAccJerkMag-mean()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAccJerkMag-mean() numeric 0 10299 10299 -0.65 0.39 -1 -0.99 -0.95 -0.3 1 ▇▁▃▂▁▁▁▁

tBodyAccJerkMag-std()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyAccJerkMag-std() numeric 0 10299 10299 -0.63 0.42 -1 -0.99 -0.93 -0.27 1 ▇▁▂▂▁▁▁▁

tBodyGyroMag-mean()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyroMag-mean() numeric 0 10299 10299 -0.61 0.4 -1 -0.98 -0.82 -0.25 1 ▇▁▃▃▁▁▁▁

tBodyGyroMag-std()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyroMag-std() numeric 0 10299 10299 -0.66 0.35 -1 -0.98 -0.83 -0.39 1 ▇▂▃▂▁▁▁▁

tBodyGyroJerkMag-mean()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyroJerkMag-mean() numeric 0 10299 10299 -0.76 0.28 -1 -0.99 -0.96 -0.55 1 ▇▃▂▁▁▁▁▁

tBodyGyroJerkMag-std()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
tBodyGyroJerkMag-std() numeric 0 10299 10299 -0.78 0.27 -1 -0.99 -0.94 -0.61 1 ▇▃▁▁▁▁▁▁

fBodyAcc-mean()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAcc-mean()-X numeric 0 10299 10299 -0.62 0.42 -1 -0.99 -0.95 -0.26 1 ▇▁▃▂▁▁▁▁

fBodyAcc-mean()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAcc-mean()-Y numeric 0 10299 10299 -0.54 0.48 -1 -0.98 -0.86 -0.1 1 ▇▁▁▃▂▁▁▁

fBodyAcc-mean()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAcc-mean()-Z numeric 0 10299 10299 -0.67 0.36 -1 -0.98 -0.9 -0.37 1 ▇▂▃▂▁▁▁▁

fBodyAcc-std()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAcc-std()-X numeric 0 10299 10299 -0.6 0.45 -1 -0.99 -0.94 -0.25 1 ▇▁▃▂▁▁▁▁

fBodyAcc-std()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAcc-std()-Y numeric 0 10299 10299 -0.53 0.48 -1 -0.98 -0.83 -0.092 1 ▇▁▁▃▂▁▁▁

fBodyAcc-std()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAcc-std()-Z numeric 0 10299 10299 -0.62 0.4 -1 -0.98 -0.84 -0.3 1 ▇▁▃▂▁▁▁▁

fBodyAcc-meanFreq()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAcc-meanFreq()-X numeric 0 10299 10299 -0.22 0.26 -1 -0.42 -0.24 -0.02 1 ▁▃▇▇▅▁▁▁

fBodyAcc-meanFreq()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAcc-meanFreq()-Y numeric 0 10299 10299 0.015 0.24 -1 -0.14 0.0047 0.18 1 ▁▁▂▇▇▃▁▁

fBodyAcc-meanFreq()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAcc-meanFreq()-Z numeric 0 10299 10299 0.047 0.28 -1 -0.14 0.061 0.25 1 ▁▁▃▇▇▅▁▁

fBodyAccJerk-mean()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccJerk-mean()-X numeric 0 10299 10299 -0.66 0.39 -1 -0.99 -0.95 -0.33 1 ▇▁▃▂▁▁▁▁

fBodyAccJerk-mean()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccJerk-mean()-Y numeric 0 10299 10299 -0.63 0.41 -1 -0.98 -0.93 -0.26 1 ▇▁▂▂▁▁▁▁

fBodyAccJerk-mean()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccJerk-mean()-Z numeric 0 10299 10299 -0.74 0.3 -1 -0.99 -0.95 -0.51 1 ▇▃▂▁▁▁▁▁

fBodyAccJerk-std()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccJerk-std()-X numeric 0 10299 10299 -0.65 0.39 -1 -0.99 -0.96 -0.32 1 ▇▁▃▂▁▁▁▁

fBodyAccJerk-std()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccJerk-std()-Y numeric 0 10299 10299 -0.61 0.43 -1 -0.99 -0.93 -0.24 1 ▇▁▂▂▁▁▁▁

fBodyAccJerk-std()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccJerk-std()-Z numeric 0 10299 10299 -0.78 0.26 -1 -0.99 -0.96 -0.59 1 ▇▃▂▁▁▁▁▁

fBodyAccJerk-meanFreq()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccJerk-meanFreq()-X numeric 0 10299 10299 -0.048 0.3 -1 -0.3 -0.045 0.2 1 ▁▂▇▆▇▅▁▁

fBodyAccJerk-meanFreq()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccJerk-meanFreq()-Y numeric 0 10299 10299 -0.21 0.27 -1 -0.43 -0.24 0.0087 1 ▁▃▇▆▆▁▁▁

fBodyAccJerk-meanFreq()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccJerk-meanFreq()-Z numeric 0 10299 10299 -0.12 0.27 -1 -0.33 -0.1 0.091 1 ▁▂▆▇▇▂▁▁

fBodyGyro-mean()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyGyro-mean()-X numeric 0 10299 10299 -0.67 0.35 -1 -0.99 -0.89 -0.38 1 ▇▂▃▂▁▁▁▁

fBodyGyro-mean()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyGyro-mean()-Y numeric 0 10299 10299 -0.71 0.34 -1 -0.98 -0.92 -0.47 1 ▇▃▂▁▁▁▁▁

fBodyGyro-mean()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyGyro-mean()-Z numeric 0 10299 10299 -0.64 0.38 -1 -0.99 -0.89 -0.32 1 ▇▁▃▂▁▁▁▁

fBodyGyro-std()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyGyro-std()-X numeric 0 10299 10299 -0.74 0.29 -1 -0.99 -0.91 -0.52 1 ▇▃▂▁▁▁▁▁

fBodyGyro-std()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyGyro-std()-Y numeric 0 10299 10299 -0.67 0.37 -1 -0.98 -0.91 -0.44 1 ▇▂▂▁▁▁▁▁

fBodyGyro-std()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyGyro-std()-Z numeric 0 10299 10299 -0.69 0.34 -1 -0.99 -0.89 -0.42 1 ▇▂▃▁▁▁▁▁

fBodyGyro-meanFreq()-X

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyGyro-meanFreq()-X numeric 0 10299 10299 -0.1 0.26 -1 -0.27 -0.099 0.068 1 ▁▁▅▇▆▂▁▁

fBodyGyro-meanFreq()-Y

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyGyro-meanFreq()-Y numeric 0 10299 10299 -0.17 0.27 -1 -0.36 -0.17 0.014 1 ▁▂▆▇▅▁▁▁

fBodyGyro-meanFreq()-Z

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyGyro-meanFreq()-Z numeric 0 10299 10299 -0.051 0.27 -1 -0.23 -0.054 0.12 1 ▁▁▅▇▆▂▁▁

fBodyAccMag-mean()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccMag-mean() numeric 0 10299 10299 -0.59 0.45 -1 -0.98 -0.88 -0.22 1 ▇▁▂▂▁▁▁▁

fBodyAccMag-std()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccMag-std() numeric 0 10299 10299 -0.66 0.36 -1 -0.98 -0.85 -0.38 1 ▇▂▃▂▁▁▁▁

fBodyAccMag-meanFreq()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyAccMag-meanFreq() numeric 0 10299 10299 0.077 0.26 -1 -0.097 0.07 0.24 1 ▁▁▂▆▇▃▁▁

fBodyBodyAccJerkMag-mean()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyBodyAccJerkMag-mean() numeric 0 10299 10299 -0.62 0.43 -1 -0.99 -0.93 -0.26 1 ▇▁▂▂▁▁▁▁

fBodyBodyAccJerkMag-std()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyBodyAccJerkMag-std() numeric 0 10299 10299 -0.64 0.41 -1 -0.99 -0.93 -0.31 1 ▇▁▂▂▁▁▁▁

fBodyBodyAccJerkMag-meanFreq()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyBodyAccJerkMag-meanFreq() numeric 0 10299 10299 0.17 0.25 -1 -0.003 0.16 0.36 1 ▁▁▁▅▇▆▂▁

fBodyBodyGyroMag-mean()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyBodyGyroMag-mean() numeric 0 10299 10299 -0.7 0.32 -1 -0.98 -0.88 -0.45 1 ▇▂▃▁▁▁▁▁

fBodyBodyGyroMag-std()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyBodyGyroMag-std() numeric 0 10299 10299 -0.7 0.31 -1 -0.98 -0.83 -0.47 1 ▇▃▃▁▁▁▁▁

fBodyBodyGyroMag-meanFreq()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyBodyGyroMag-meanFreq() numeric 0 10299 10299 -0.042 0.28 -1 -0.23 -0.052 0.15 1 ▁▁▅▇▆▃▁▁

fBodyBodyGyroJerkMag-mean()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyBodyGyroJerkMag-mean() numeric 0 10299 10299 -0.78 0.27 -1 -0.99 -0.95 -0.61 1 ▇▃▁▁▁▁▁▁

fBodyBodyGyroJerkMag-std()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyBodyGyroJerkMag-std() numeric 0 10299 10299 -0.79 0.26 -1 -0.99 -0.94 -0.64 1 ▇▃▁▁▁▁▁▁

fBodyBodyGyroJerkMag-meanFreq()

Distribution

0 missing values.

Summary statistics
name data_type missing complete n mean sd p0 p25 p50 p75 p100 hist
fBodyBodyGyroJerkMag-meanFreq() numeric 0 10299 10299 0.13 0.25 -1 -0.019 0.14 0.29 1 ▁▁▁▅▇▅▁▁

Missingness report

Among those who finished the survey. Only variables that have missing values are shown.

## Warning: Could not figure out who finished the surveys, because the
## variables expired and ended were missing.

Codebook table